Differences in information accessed in a pharmacologic knowledge base using a conversational agent vs traditional search methods.

Introduction: Clinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, an artificial intelligence-based conversational agent, Watson Assistant (WA), was made available to online subscribers to the pharmacologic knowledge base, Micromedex®. WA allows users to ask medication-related questions in natural language.

Artificial intelligence-based conversational agent to support medication prescribing.

Objective: This article describes the system architecture, training, initial use, and performance of Watson Assistant (WA), an artificial intelligence-based conversational agent, accessible within Micromedex.

Materials And Methods: The number and frequency of (target of a user's query) triggered in WA during its initial use were examined; intents triggered over 9 months were compared to the frequency of topics accessed via keyword search of Micromedex. Accuracy of WA intents assigned to 400 queries was compared to assignments by 2 independent subject matter experts (SMEs), with inter-rater reliability measured by Cohen's kappa.

Age and Other Risk Factors Influencing Long-Term Mortality in Patients With Traumatic Cervical Spine Fracture.

Objective: To identify clinical or demographic variables that influence long-term mortality, as well as in-hospital mortality, with a particular focus on the effects of age.

Summary And Background Data: Cervical spine fractures with or without spinal cord injury (SCI) disproportionately impact the elderly who constitute an increasing percentage of the US population.

Methods: We analyzed data collected for 10 years at a state-designated level I trauma center to identify variables that influenced in-hospital and long-term mortality among elderly patients with traumatic cervical spine fracture with or without SCI.